five

Parkes observations for project P1014 semester 2020APRS_03

收藏
Research Data Australia2024-12-14 收录
下载链接:
https://researchdata.edu.au/parkes-observations-project-semester-2020aprs03/1605768
下载链接
链接失效反馈
官方服务:
资源简介:
The spatial distribution of neutral gas is important for understanding the interstellar medium (ISM), its evolution, and star formation. However, the distribution of Tiny Scale Atomic Structures (TSAS), especially the extremely small scale structures with spatial scales ranging from a few to hundreds of AU is largely unexplored. The formation and evolution of TSAS are still unknown. Multi-epoch observations of HI absorption against pulsars are a tested, practical observational method to probe the TSAS. Based on our observations in the 2019 APRS semester, we successfully processed baseband data and detected the HI absorption variation at over 4-months towards B1557-50. PSR B1451-68 is another ideal source to trace the TSAS because of the intervening cold gas. We thus propose one-epoch observation towards B1557-50 which should be as early in the semester as possible, and two-epoch observations towards B1451-68 to be separated by about 5 months, for monitoring the HI absorption variations and probing structures on a range of scales. This will better constrain the characteristics of variations in HI absorption, thus contribute significantly to understanding the origin of TSAS.

中性气体的空间分布对于理解星际介质(interstellar medium,ISM)、其演化过程以及恒星形成机制均具有关键意义。然而,小尺度原子结构(Tiny Scale Atomic Structures,TSAS)的分布,尤其是空间尺度为数个至数百天文单位(AU)的超小尺度结构,在很大程度上仍未得到充分探索。小尺度原子结构的形成与演化机制至今仍不明朗。以脉冲星为背景的氢原子(HI)吸收多历元观测,是一种经实践验证的可靠观测方法,可用于探测小尺度原子结构。基于2019年APRS学期的观测数据,我们已成功完成基带数据处理,并在朝向PSR B1557-50的观测中检测到跨度超过4个月的氢原子吸收变化。PSR B1451-68则是另一理想的小尺度原子结构探测源,因其视线方向存在前景冷气体。因此,我们提议对PSR B1557-50开展单次历元观测(应尽可能安排在学期初期),并对PSR B1451-68开展两次历元观测(两次观测间隔约5个月),以监测氢原子吸收的变化并探测不同尺度的结构。该观测计划将更好地约束氢原子吸收变化的特征,从而为理解小尺度原子结构的起源提供重要支撑。
提供机构:
Commonwealth Scientific and Industrial Research Organisation
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作